{"id":"W4388717346","doi":"10.48550/arxiv.2311.08270","title":"A consensus-based algorithm for non-convex multiplayer games","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Karl-Franzens-Universität Graz; European Commission","keywords":"Initialization; Computer science; Mathematical optimization; Convergence (economics); Swarm behaviour; Game theory; Regular polygon; Cournot competition; Limit (mathematics); Nash equilibrium; Algorithm; Mathematics; Mathematical economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005438855,0.0005882733,0.0007757643,0.0004746071,0.0002126553,0.0002726775,0.002736218,0.0005290274,0.0000107743],"category_scores_gemma":[0.0001142677,0.0006952727,0.0006169827,0.000665067,0.0001399596,0.0001709261,0.0012465,0.0005177952,0.0003894776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003442158,"about_ca_system_score_gemma":0.0005719066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003259619,"about_ca_topic_score_gemma":0.0000570219,"domain_scores_codex":[0.9964449,0.000176835,0.0004434995,0.001963869,0.000189646,0.0007812493],"domain_scores_gemma":[0.9958979,0.0007761666,0.0005202024,0.002006778,0.0004816613,0.0003172171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004440294,0.001471094,0.007339868,0.001981637,0.003355685,0.006206897,0.001049176,0.8086844,0.0008153967,0.05803698,0.04961078,0.06100406],"study_design_scores_gemma":[0.002868379,0.0000676719,0.0005588239,0.0001865883,0.0001065117,0.000003078233,0.00006149725,0.9899992,0.0002749818,0.002771863,0.002374307,0.0007271005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006571229,0.00004069022,0.9870747,0.0003449317,0.002479962,0.001718638,0.0005973903,0.0009667623,0.0002057148],"genre_scores_gemma":[0.9669363,0.00001633259,0.02798394,0.0001912491,0.0002031671,0.00003618376,0.0001751486,0.00007140262,0.004386294],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9603651,"threshold_uncertainty_score":0.9995499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09412424359455232,"score_gpt":0.21218545481453,"score_spread":0.1180612112199776,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}